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MathlibNt.AnalyticNumberTheory.Vaughan.VaughanDirectTypeIPhysicalScale

Direct Vaughan Type-I: the AP-normalized physical scale #

The unsquared mean arising from character orthogonality has weight 1 / φ(q). This module keeps that weight through row Cauchy and only then invokes the existing variable-length primitive maximal large sieve. It also records why putting the square-large-sieve weight q / φ(q) on the unsquared mean inserts an extra factor q before any analytic estimate is used.

The primitive unsquared mean with the weight produced by AP character orthogonality. This is deliberately distinct from the square-large-sieve weight q / φ(q).

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    The old unsquared weight is exactly q times the AP-normalized summand.

    Strict one-level scale counterexample: as soon as the primitive amplitude mass is positive and q>1, replacing 1/φ(q) by q/φ(q) strictly enlarges that level. Thus q/φ(q) cannot be called the direct AP-normalized L¹ mean; it is the square-large-sieve weight.

    noncomputable def AnalyticNumberTheory.LargeSieve.apNormalizedVariableLengthRowMean {ι : Type u_1} [DecidableEq ι] (S : Finset ι) (c : ι) (L : ι) (Q : ) :

    Rowwise AP-normalized L¹ majorant. For Vaughan's first lane, S is a d-shell; for the middle lane it is a (d,e) shell.

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      theorem AnalyticNumberTheory.LargeSieve.apNormalizedVariableLengthRowMean_sq_le {ι : Type u_1} [DecidableEq ι] (S : Finset ι) (c : ι) (L : ι) (Q : ) (hcard : qFinset.Icc 1 Q, Fintype.card (PrimitiveCharacter q) q.totient) :
      apNormalizedVariableLengthRowMean S c L Q ^ 2 (Finset.Icc 1 Q).card * S.card * qFinset.Icc 1 Q, (↑q.totient)⁻¹ * χ : PrimitiveCharacter q, rS, primitiveCharacterPrefixMaxSquare (c r) 0 (L r) q χ

      Cauchy with the correct normalization. The exact number of rows and moduli is visible; no analytic hypothesis is hidden here.

      theorem AnalyticNumberTheory.LargeSieve.apNormalized_variableLength_square_le_budget {ι : Type u_1} [DecidableEq ι] (S : Finset ι) (c : ι) (L : ι) (Q : ) (hQ : 0 < Q) :
      qFinset.Icc 1 Q, (↑q.totient)⁻¹ * χ : PrimitiveCharacter q, rS, primitiveCharacterPrefixMaxSquare (c r) 0 (L r) q χ variableLengthPrimitivePrefixBudget S c L Q

      The AP-normalized square ledger is bounded by the existing variable-length large sieve. This is the precise point where the proved LS theorem is called.

      Combined corrected-weight Cauchy + variable-length LS producer.

      The middle μ*Λ lane retains the literal Λ square energy; it is not silently replaced by a row count.

      theorem AnalyticNumberTheory.LargeSieve.corrected_typeI_shell_physical_of_square (shellMean logPay N Q : ) (hmean : 0 shellMean) (hlog : 0 logPay) (hN : 0 N) (_hQ : 0 Q) (hsq : shellMean ^ 2 (logPay * (N + Q ^ 2 * N)) ^ 2) :
      shellMean logPay * (N + Q ^ 2 * N)

      Scalar shell optimization. If a corrected-weight shell has a square bound , then it has the physical unsquared bound P; choosing P = logPay * (N + Q² sqrt N) is the exact producer shape.